Forward Deployed Engineering Lead, Applied AI & Engineering

Citi

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Irving, TX
Salary: $156,160–$234,240 / yr
Posted: 6 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $193k

This role $195k

$127k most similar roles pay here $248k

This role pays more than 55% of similar roles. Most pay $161,250–$225,625 — the shaded band above. At the midpoint, this role pays about $195k versus about $193k for comparable roles.

Based on 240 similar postings.

Employer

About Citi

Citi is one of the world’s most trusted financial institutions, proudly serving millions of customers across the United States.

Citi currently has 265 open roles on FindRole.

Listed pay typically runs $138,720–$208,080 across 247 roles with salary data.

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At a glance

TL;DR · Forward Deployed Engineering Lead, Applied AI & Engineering

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Forward Deployed Engineering Lead (SVP - Applied AI & Engineering) serves as a strategic technical leader within the Client Network Services team, focusing on the development of agentic AI solutions. This role involves building out Chorus for CNS by collaborating directly with stakeholders to translate complex business challenges into production-grade systems. The successful candidate will lead a high-performing engineering team while remaining deeply involved in architecture and code. Key responsibilities include designing agentic AI using Google Agent Development Kit (ADK) and Model Context Protocol (MCP) Servers, developing full-stack applications with Python, Java, and React, and managing infrastructure on Kubernetes. The role also requires implementing OAuth 2.0 security via HashiCorp Vault and ensuring operational excellence through DORA metrics. This position solves the challenge of integrating advanced AI capabilities into enterprise workflows to streamline operations and maintain a competitive advantage.

Skills

Python Java React Kubernetes Docker AWS Google Cloud Platform Terraform Helm Snyk Vault Prometheus Grafana Kafka PostgreSQL MongoDB Redis DynamoDB OAuth 2.0 CI/CD SDLC

What you'll do

Define the technical strategy, architecture, and delivery roadmap for Chorus within Client Network Services.
Design and build agentic AI solutions using Google Agent Development Kit and Model Context Protocol.
Develop scalable APIs and backend services using Python and Java while building front-end interfaces with React.
Implement secure authentication and authorization solutions using OAuth 2.0 and HashiCorp Vault for secret management.
Deploy, operate, and maintain production-grade services on Kubernetes using cloud-native architecture principles.
Lead, mentor, and develop a high-performing engineering team while maintaining active involvement in code and architecture.
Manage the full software development lifecycle by championing SDLC best practices and tracking DORA metrics.
Partner with senior stakeholders to translate complex business requirements into technical execution and roadmap alignment.

What we're looking for

Bachelor's/University degree or equivalent experience in Computer Science, Engineering, or a related technical field.
Demonstrated success as a Senior Engineering Leader, Engineering Manager, or Technical Architect with a track record of leading and scaling high-performing teams.
Deep hands-on experience developing Agentic AI solutions using Google Agent Development Kit (ADK) and Model Context Protocol (MCP) Servers.
Expert-level proficiency in Python and Java for API design, microservices development, and distributed systems.
Advanced front-end development expertise using React, including state management and performance optimization.
Deep understanding of OAuth 2.0 authentication and authorization frameworks, including token-based security and identity management.
Extensive experience architecting, deploying, and operating services on Kubernetes with a focus on cloud-native architecture.
Proficiency in infrastructure-as-code tools like Terraform or Ansible and experience with HashiCorp Vault for secrets management.

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